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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
A delayed plant disease model with Caputo fractional derivatives
Advances in Continuous and Discrete Models, Volume 2022, No. 1, Article 11, Year 2022
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Description
We analyze a time-delay Caputo-type fractional mathematical model containing the infection rate of Beddington–DeAngelis functional response to study the structure of a vector-borne plant epidemic. We prove the unique global solution existence for the given delay mathematical model by using fixed point results. We use the Adams–Bashforth–Moulton P-C algorithm for solving the given dynamical model. We give a number of graphical interpretations of the proposed solution. A number of novel results are demonstrated from the given practical and theoretical observations. By using 3-D plots we observe the variations in the flatness of our plots when the fractional order varies. The role of time delay on the proposed plant disease dynamics and the effects of infection rate in the population of susceptible and infectious classes are investigated. The main motivation of this research study is examining the dynamics of the vector-borne epidemic in the sense of fractional derivatives under memory effects. This study is an example of how the fractional derivatives are useful in plant epidemiology. The application of Caputo derivative with equal dimensionality includes the memory in the model, which is the main novelty of this study. © 2022, The Author(s).
Authors & Co-Authors
Kumar, Pushpendra
India, Puducherry
National Institute of Technology Puducherry
Bǎleanu, Dumitru I. I.
Turkey, Ankara
Çankaya Üniversitesi
Romania, Bucharest
Institute for Space Sciences, Bucharest
Ertürk, Vedat Suat
Turkey, Samsun
Ondokuz Mayis Üniversitesi
Inç, Mustafa
Turkey, Istanbul
Biruni Üniversitesi
Turkey, Elazig
Firat Üniversitesi
Taiwan, Taichung
China Medical University
Govindaraj, Venkatesan
India, Puducherry
National Institute of Technology Puducherry
Statistics
Citations: 23
Authors: 5
Affiliations: 7
Identifiers
Doi:
10.1186/s13662-022-03684-x
ISSN:
27314235
Study Design
Cross Sectional Study